Triple
T6101869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Badmotorfinger |
E136015
|
entity |
| Predicate | notableTrack |
P8087
|
FINISHED |
| Object | Rusty Cage |
E136019
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Rusty Cage | Statement: [Badmotorfinger, notableTrack, Rusty Cage]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rusty Cage Context triple: [Badmotorfinger, notableTrack, Rusty Cage]
-
A.
Rusty Cage
chosen
"Rusty Cage" is a high-energy, riff-driven rock song by Soundgarden, widely recognized as one of the standout tracks of the early 1990s grunge era.
-
B.
Cage
Cage is a surname most famously associated with avant-garde American composer John Cage, a pioneer of experimental and minimalist music.
-
C.
Cage
Cage is an American underground rapper known for his dark, introspective lyrics and influential role in alternative hip hop.
-
D.
Caged
Caged is a 1950 American film noir-style women-in-prison drama noted for its stark realism and strong performances.
-
E.
The Golden Cage
The Golden Cage is a non-fiction book by Iranian Nobel Peace Prize laureate Shirin Ebadi that recounts the tragic, intertwined fates of three brothers whose lives reflect the political turmoil of modern Iran.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c0087dee9881909e3655be88208c01 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05b3c073c81908248c799934d6fce |
completed | March 22, 2026, 9:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1359334c081909653603633ba9c06 |
completed | March 23, 2026, 12:44 p.m. |
Created at: March 22, 2026, 4:13 p.m.